1. Field of the Invention
The present invention relates generally to a receiver in a communication system, and in particular, to a device and method for quantizing a received signal.
2. Description of the Related Art
System resources such as bit number, power, and process delay are limited when a channel decoder is constructed in a real situation. A specific signal must be represented by a limited number of bits, particularly for processing in a decoder. In other words, the analog signal applied to the input of the decoder must be quantized. Signal resolution or signal precision should be considered for quantization because it has a great influence on the performance of the decoder. Accordingly, a quantization method involving accurate selection of the number of quantization bits (QB) is a significant challenge to a system designer when he represents the signals for the input terminal of a decoder and inside the decoder.
A transmitter in a radio communication system (e.g., satellite system, WCDMA, CDMA-2000) can use forward error correction codes for reliable data transmission, and a receiver can apply iterative decoding to received data. The iterative decoding is characterized by feeding decoded output back to the input of a decoder. Therefore, the output of an iterative decoder is not a hard-decision signal like a high or low signal (e.g., +1, −1) but a soft-decision signal (e.g., 0.7684, −0.6432, . . . ). The iterative decoder is constituted out of at least two component decoders and an interleaver which is located between the component decoders and permutes the sequence of bits received from the component decoder at its input end. When decoded signal components are fed back to the output terminal of the iterative decoder, the deinterleaver of the iterative decoder reorders the bits of the interleaved signal in their original positions.
FIG. 1 is a graph illustrating a quantization method in a conventional Viterbi decoder for transmission of a voice signal.
In FIG. 1, the horizontal axis of the graph indicates the amplitude levels of a received signal, and a vertical axis indicates the probability density functions (PDFs) of the two signals. It is assumed herein that a transmission channel for the received signal is an additive white Gaussian noise (AWGN) channel. The received and demodulated signal is quantized at predetermined intervals with respect to the PDF. This quantization is generally utilized due to its advantages of simplicity and good decoding performance. As shown in FIG. 1, QB is 4 bits and the resulting quantization levels (QL) are used to represent the range between +A and −A which are the levels of a signal received from a transmitter. For example, though the received signal may have a value above +A or below −A due to noise on a transmission channel, it is mapped to a maximum quantization level (QMAX) or minimum quantization level (QMIN), respectively.
A Viterbi decoder basically employs a non-iterative decoding scheme and outputs a hard-decision value, which is not re-decoded. Therefore, the Viterbi decoder can decode an input signal with sufficient reliability in the above quantization method. When the QB is set to 4 (QL=16), the performance difference between the Viterbi decoding and infinite level decoding is no more than 0.2 dB.
On the other hand, the input/output of an iterative decoder is based on soft-input/soft-output (SISO). Hence, confidence as well as polarity should be considered in the design of the input of the decoder. That is, the output signal of the SISO iterative decoder that will be fed back should be not a hard-decision signal (high or low) but a soft decision signal. But signals beyond the transmission level range from +A and −A are truncated during analog-to-digital conversion in the conventional quantization method described in FIG. 1, resulting in a serious degradation of the performance of the iterative decoder. Therefore, different levels must be assigned to the signals above +A and below −A, which are applied to the input of the iterative decoder. In order words, the quantization range should be expanded beyond the transmission level range between +A and −A, so that the reliability for an input signal of the iterative decoder is differentiated.
When representation levels of an input signal are allocated as in the conventional quantization method of FIG. 1, the insufficient quantization resolution resulting from expansion of the quantization range is likely to degrade the performance of the iterative decoder. Hence, the optimal QB should be determined.
Especially, though a BPSK (Binary Phase Shift Keying) or QPSK (Quadrature Phase Shift Keying) demodulation signal applied to a turbo decoder in a receiver is generally an analog signal, criteria on which to obtain parameters for quantizing the analog signal should be presented when a turbo decoder is configured in real VLSIs.